Automatic Number Pate Recognition System Information Technology Essay

spontaneous Number Pate Recognition System cultivation Technology Essay machine comparable number pate information strategy is a mass surveillance method that lend oneselfs optical fiber experience on escorts to get the license ingathering shells on vehicles. System might skitter number graduated tables at somewhat one per second on gondola railway cars travelling up to 100mph(160 km/h).they can theatrical role existing closed -circuit tele raft eagerness or road-rule enforcement photographic cameras, or ones specifically designed for the task. They are use by various jurisprudence forces and as a method of electronic monetary value collection on apply-per-use roads and monitor barter activity, such(prenominal) as red light adherence in an intersection.ANPR can be utilise to store the get winds capture by the cameras as well as the school text from the license scurf, with some configurable to store a photograph of the sweatr. Systems commonly use infrare d lighting to al humble the camera to take the picture at any magazine of the day. A powerful flash is inclined in at least one version of the intersection-monitoring cameras, serving both to irradiate the picture and to make the offender aware of his or her mistake. ANPR applied science tends to be region -specific, owing to pate variation from place to place.Some concerns some these dodgings fill centered on privacy fears of g overnment tracking citizens runs and media reports of misidentification and lofty error rates. However, as they have developed, the ashess have become much more than(prenominal)(prenominal) accurate and reliable. thither is an increasing requirement to identify vehicles and track their arrangement for a wide number of applications. These includeCongestion charging Several major(ip) cities somewhat the world levy a debase a drive within themCar park management Using the number family to identify the condemnation of entry and departure of aVehicle.Counter-terrorism Monitoring the arrival and departures of vehicles at major ports.Literature ReviewOur literature survey generally foc utilize on automatic number scale of measurement clay look into papers and its existing system along with its application, regard process proficiency and aflutter interlock recognition. These can be clearly illustrated as followsAutomatic number plate recognition systemJavaanpr existing open origination tag in sourceforge.netThesis describing research, enter touch on and aflutter vaneing technique along with its algorithm in pdf on umberanpr on sourceforge.net go for process techniqueImageJ -api establish on burnt umber language for digital digit processingImage editor program -api establish on java language made for ikon processingJAI api -java advance mental imagery for image processing from sunmicrosystem atjava.sun.com.Opencv-Digital Image Processing (text bulk from subroutine library)Neural net exertioning tech niqueIntroduction to java neural network second edition by jfheaton at heatonresearch.comSome ocr samples utilise neuralnetworking at sourcecode.com and its explanationStudy on nepali ocr research conducted by madan puraskar guthi(yala Maya Kendra)Ocr sample developed by Google based for Linux accessible for windows on dot net (tesseract)Joone locomotive-java api on neural network not so well developed and efficient athttp//www.joo saucilyfangledorld.comKohenen -java api on self organizing map applied to agitate jpeg image.Somdemo-sample java program for fiction how self organizing map works.Program iterately train to converge with identical chroma from random samplesArtificial neural network text book available at library (low price edition from pearsoneducation.Neural networks systematic origin by Raul Rojas(from point outs at free university at Berlin and later at the university of Halle)Automatic Number Pate Recognition systema)javaanprJavaanpr open source available at sourceforge.net worked as prototype for building our Nepalese automatic Nepali number plate recognition system. It overly contain thesis in pdf format prescribing image processing technique and neural networking technique along with its algorithm. It works well recognizing foreign number plates contained as sample in the site. It was beautifully coded enforceing sophisticated and specialized algorithms for image processing and neural network technique. It also utilise xml files to save and retrieve neural network reading data. realise sample javaanpr at sourceforge.netFor more information-http//sourceforge.netImage processing proficiencya)ImageJ 1.42ImageJ was prototypic developed on class files now available on graphical user interface interface. User can just process image using various buttons and entries if prescription is required .programmers can develop own macros and plugins to execute its intended function if required and compile there within and run short the code.I t is capable of processing both 2D and 3D interactive image processing.Figure. ImageJ graphical window interfaceFor more information http//rsb.info.nih.gov/ij/b) Image editorImage editor was also found during search for image processing tool. It is also based on java language and available as java API, now class file are available with GUI interface easing its its purpose. Image editor api seems inefficient and not so capable for our intended operation and not so much researched.C) JAI apithe java advance imaging(JAI) API further extends the java platforms (including the java 2D API) by allowing sophisticated, gritty -performance image processing to be incorporated into java applets and applications.JAI is a set of classes providing imaging functionality beyond that of Java 2D and the Java Foundation classes, though it is compatible with those APIs.JAI implements a set of core image processing capabilities including image tiling, regions of interest, and deferred execution.JAI als o offers a set of core image processing operators including many another(prenominal)(prenominal) common point, area, and frequency-domain operators.JAI is intended to meet the needs of all imaging applications. The API is exceedingly extensible, allowing hot image processing operations to be added in such a way as to appear to be a inherent part of it. Thus, JAI benefits virtually all Java developers who want to incorporate imaging into their applets and applications.JAI featuresCross-platform imagingDistributed ImagingObject-oriented APIFlexible and ExtensibleDevice Independent brawnyHigh PerformanceInteroperableInitially program steganography was through in JAI Later it becomes little inefficient and we again go for another programming method.For further information-http//java.sun.comd) Digital Image processing (text book from library)e) OpencvThe OpenCV implements a wide variety of tools for image interpretation. It is compatible with Intel Image Processing program library (IPL) that implements low-level operations on digital images. In spite of primitives such as binarization, filtering, image statistics, pyramids, OpenCV is mostly a high-level library implementing algorithms for calibration techniques (Camera Calibration), feature detection (Feature) and tracking (Optical Flow),shape analysis(Geometry, Contour Processing ),motion analysis (Motion Templates, Estimators ), 3D reconstruction (View Morphing),object variance and recognition (Histogram, Embedded Hidden Markov Models, Eigen Objects).The essential features of the library along with functionality and quality is performance. The algorithms are based on highly pliable data structures (Dynamic Data Structures) coupled with IPL data structures more than a one-half of the functions have been assembler optimized taking advantage of Intel Architecture (PentiumMMX,Pentium Pro, PentiumIII, Pentium4).Why We motive OpenCV LibraryThe OpenCV Library is a way of establishing an open source vision com munity thatWill make better use of up-to- booking opportunities to apply estimator vision in theGrowing PC environment. The packet provides a set of image processing functions,As well as image and pattern analysis functions. The functions are optimized for IntelArchitecture processors, and are particularly useful at taking advantage of MMXTechnology.The OpenCV Library has platform-independent interface and supplied with whole C root systems. OpenCV is open.Relation in the midst of Opens and Other LibrariesOpenCV is designed to be used unneurotic with Intel Image Processing Library (IPL)And extends the latter functionality toward image and pattern analysis. Therefore,OpenCV shares the comparable image format (IplImage) with IPL.Also, OpenCV uses Intel Integrated Performance Primitives (IPP) on lower-level, ifIt can settle the IPP binaries on startup.IPP provides cross-platform interface to highly-optimized low-level functions thatPerform domain-specific operations, particularl y, image processing and computerVision primitive operations. IPP exists on multiple platforms including IA32, IA64,And StrongARM.Source-openCV reference manual.pdfCmgui-wx-2(.net negligee class)This openCV tool can be easily integrated with .net platform like c, visual basic etc.Cmgui is an advanced 3D visual image software package with modeling capabilities.Cmgui is a part of CMISS, a mathematical modeling environment initially developed by the University of Auckland Bioengineering Institute.CMISS stands for Continuum Mechanics, Image analysis. Signal processing and System Identification. There are three major CMISS software packages. Broadly speaking the main areas severally piece of software deals with are as followsCM is used for computational modelingUnemap is used for signal acquisition and processingCmgui is used for model visualization and manipulationFor more information-wiki/getting started with cmguiNeural Networking techniquea) Introduction to java neural network by jeff heatonThis book along with video lecture serve uped very much for us to understand neural networks and learn mark technique. It was published form Heaton research center and they have developed encog mannequin for neural network where programmer can build fast neural network prototype for fast screening and checking since easy and flexible. After parameters have been determined for best operation such as number of out of sight layers and number of neurons in each layer coding can be done since it code exit be inflexible for such modification. hold up contained different chapters on various types of neural networks and also its application. Only first seven chapters are allowed to read online and rests are not. It provides all its source code on site which also helps in learning and testing.Same book is also available in c language.For more information-http//heatonreasearch.com/b) On the starting of project research we also got OCR sample using neural network at sourceco de.com with explanation. It was written at c, due to compiler conundrum I didnt stress here much.c) Nepali OCRFor us it was good parole service and opportunity to study research on Nepali OCR conducted by madan puraskar guthi. polar research papers were available on the site along with image processing portion code used to fragment Nepali character Image written on java. It deals with problem issues and complexity faced on Nepali character like devnagari font.For more information -http//d) OCR engine tessaract by GoogleThis was used by Nepali OCR for its processing and it supports many languages like Hindi, Nepali, Urdu, arabi etc. we didnt research here much.Figure segmented portion ofFigure some other segmented portion ofFor more information-make Google search for linkd) joone enginejoone engine as a api in hope for easy and efficient coding we consider but it seems unworthy for project work. For beginner liking to test some xor operations and akin(predicate) whitethorn fi nd at least satisfactory otherwise unworthy.For more information-http//www.jooneworld.com/docs/engine.htmle)KohenenThis sample also seems beautiful in understanding self organizing map or kohenen network. Here it is used to compress jpeg image. It was programmed on seven packages.For more information-http //f) som demoThis sample tries to converge iteratively with similar colors from randomly scattered pixel colors based on Euclidean distance method.Figure som ahead trainingFigure som afterward trainingFor more information-link available at reference http//www.ai-junkie.com/ann/som/g) Artificial neural Network text book (library)h) Neural network systematic universe (by Raul Rojas)This book is good for understanding neural network systematically and based on lectures at free university at Berlin and later at the University of Halle.For more introduction-reference at http//www.wikipedia.com/selforganisingmapFigure sample kohenen neural network (3D kohenen feature map)Source http// rfhs8012.fh-regensburg.de/jfroehl/index.htmlAnpr system application around world guard enforcementGermanyOn 11 March 2008, the Federal Constitution Court of Germany ruled that the laws permitting the use of automatize number plate recognition systems in Germany violated te pay to privacy.HungarySeveral Hungarian Auxiliary Police units use a system called Matrix Police in cooperation with the police. It consists of a portable computer fit out with a webcam that scans the stolen car database using automatic number plate recognition. The system is installed on the dashboard of selected patrol vehicles (PDA based handled versions exists as well) and is mainly used to control the license plate of parking cars, as the Auxiliary Police doesnt have the authority to station moving vehicles to stop. If a stolen is found, the formal police are informed.United KingdomThe UK has an extensive (ANPR) automatic number plate recognition CCTV network. Effectively, the police and security services track all car movements around the country and are able to track any car in close to real time. Vehicle movements are stored for 5 geezerhood in the National ANPR Data Centre to be analyzed for intelligence and to be used as evidence.USAIn the USA, ANPR systems are more commonly referred to as LPR (License photographic plate Reader or License Plate Recognition) technology or ALPR (Automatic License Plate Reader/Recognition) technology.One of the biggest challenges with ALPR technology in the US is the accuracy of the Optical Character Recognition (OCR)-the unquestionable identification of the characters on the license plate.From time to time, states will make evidential changes in their license plate protocol that will affect OCR accuracy. They may add a character or add a new license plate design. ALPR systems must adapt to these changes quickly in order to be effective.In addition to the real-time processing of the license plate numbers, some ALPR systems in the US collect da ta at the time of each license plate capture .Data such as date and time stamps and GPS coordinates can be reviewed in relation to investigations and can help lead to critical breaks such as placing a comical at a scene, witness identification, pattern recognition or the tracking of suspect individuals.Average Speed camerasAnother use of ANPR in the UK, Italy and Dubai (UAE) is for promote cameras which work by tracking vehicles travel time between two restore points ,and therefore calculate the ordinary expedite. These cameras are claimed to have an advantage over traditional speed cameras in maintaining steady legal speeds over widen distances, rather than encouraging heavy braking on approach to specific camera locations and subsequent acceleration back to illegal speeds.UKThe longest stretch of average speed cameras in the UK is found on the A77 road in Scotland, with 30 miles (48 km) being monitored between Glasgow and Ayr.ItalyIn Italian highways has developed a monitor ing system named Tutor covering more than 1244 km (2007). Further extensions will add 900 km before the end of 2008.The Tutor system is also able to intercept cars while changing lanes.Traffic control numerous cities and district have developed traffic control systems to help the movement and flow of vehicles around the road network. This had topically involved looking at historical data, estimates, observations and statistics such asCar park usage walker crossing usageNumber of vehicles along a roadAreas of low and high congestionFrequency, location and cause of road wordsThe UK companionship Traffic master has used ANPR since 1998 to estimate average traffic speeds on non-motorway roads without the results being skewed by local fluctuations caused by traffic lights and similar. The company now operates a network of over 4000 ANPR cameras ,but claims that only the quad most central digits are identified , and no number plate data is retained.Electronic toll collectionOntarios 407 ETR highway uses a faction of ANPR and radio transponders to toll vehicles entering and exiting the road. Radio antennas are located at each junction and detect the transponders, logging the unique identify of each vehicle in much the same way as the ANPR system does.There are numerous other electronic toll collection networks which use combination of Radio frequency identification and ANPR. These include twosome pass for the apotheosis John Harbor Bridge in Saint John New BrunswickCity link Eastlink in Melbourne, AustraliaGateway state highway and Logan Motorway, Brisbane , AustraliaFast Trak in California ,United statesHighway 6 in IsraelTunnels in Hong Kong etcCharge zones the London congestion mienThe London congestion charge is an example of a system that charges automobilists entering a payment area. hug drug for London (TFL uses ANPR systems and charges motorists a daily fee of 8 paid before 10pm if they enter, leave or move around within the congestion charge zone.St ockholm congestion taskIn Stockholm, Sweden, ANPR is used for the congestion tax of cars driving into or out of the inner city must pay a charge, depending on the time of the day.Other usesANPR systems may also be used for/bySection control, to measure average vehicle speed over longer distances.Border crossingsFillings stations to log when a motorist drives away without paying for their fuel.A marketing tool to log patterns of useTraffic management systems, which determine traffic flow using the time it takes vehicles to pass two ANPR sites.Drive Through Customer Recognition, to automatically pick out customers based on their license plate and offer them their last selection, meliorate service to the customerTo assist visitor management systems in recognizing node vehicles.Circumvention Techniques (drawback)Vehicles owners have used a variety of techniques in an attempt to shelve ANPR systems and road -rule enforcement cameras in general. These methods may beIncreasing reflect ive properties of the garner and so that system might no locate or bewilder high enough level of contrast to be able to readUse of plate cover or sprayUse of diddlyshit to smear their license plate or utilize covers to mask the plateANPR imaging hardwareThe frontend of any Imaging hardware is image capturing bend that is camera. Retroreflective camera returns the light back to the source and thus improves the contrast of the image. A camera that makes use of active infrared imaging (with a approach pattern color filter over the lens and infrared illuminator next to it) benefits greatly from this as the infrared waves are reflected back from the plate. This is only possible on dedicated ANPR cameras, however, and so cameras used for other purposes must rely more heavily on the software capabilities.Figure hardware components used in ANPR systemFigure source-http//securityautomation.co.ukTo avoid blurring it is ideal to have the shutter speed of a dedicated camera set to 1/1000th of a second. License plate capture cameras can now produce operating(a) images from vehicles traveling at 120 mph (190 km/h).threshold angles of incidence between camera lens and license plate are also major consideration to avoid image distortion during installation. Manufacturers have developed tools to lead errors from the physical installation of license plate capture cameras.Research on down sampling characterFor neural network input character image is down sampled into intercellular substance whose value is binary 1 or 0 according to Boolean property of character on matrix region.It showed that no of samples required is not fixed and it varies with thickness of font traced.Figure down sampling image character o with 7*5 matrixFigure downsampling same character image o (buffered) with 32 *35 matrixResearch works on algorithmsA new algorithm for character cleavage of license plateCharacter part is an important step in License Plate Recognition (LPR) system. There are many di fficulties in this step, such as the influence of image noise, plate frame, rivet, the space mark, and so on. This new algorithm presents character section using Hough transformation and the prior knowledge in horizontal and erect segmentation respectively. Furthermore, a new object enhancement technique is used for image preprocessing. The experimentation results show a good performance of this new segmentation algorithm. algorithmic rule (steps)PreprocessingSize normalizationDetermination of plate kindlyObject enhancementHorizontal segmentation using Hough transformation perpendicular segmentationFor more information-a new algorithm for character segmentation of license plate.pdfan adaptational thresholding algorithm for the augmented reality toolkitIt is well cognise that fixed global thresholds have adverse effects on the dependableness of stain-based optical trackers under non-uniform lighting conditions. Mobile augmented reality applications, by their very nature, deman d a certain level of robustness against change external illumination from visual tracking algorithms currently AAR Toolkit depends on fixed-threshold image-binarization in order to detect candidate fiducials for further processing. In an effort to asperse tracking failure due to uniform shadows and reflections on a marker approach, a fast algorithm for selecting adaptive threshold values, based on the arithmetic compressed of pixel intensities over a region-of- interest around candidate fiducials.AlgorithmThis works on a per-marker basis and evaluates the mean pixel luminance over a thresholding region-of -interest (ROI), which is defined as bounding rectangle around the markers axis -aligned corner vertices in screen space. If a marker has been notice in any attached frame, its bounding rectangle will be used as thresholding -ROI prediction for successive frames. This method yields good thresholding level in practice, given sufficiently high video frame rates.Fig.1.reflection off a markers surface with adaptive thresholding (upper) and a global threshold (lower)For more information-10.1.1.9.4636.pdfadaptive license plate image extractionThis paper represents the automatic plate localization component of a car license plate recognition system. The approach concerns stages of preprocessing, edge detection, filtering, detection of the plates position, slope evaluation, and character segmentation and recognition. superstar gray-level images are used as the only source of information. In the experiments Israeli and Bulgarian license plates were used, camera obtained at different daytime and whether conditions.Algorithm (step)preprocessing for plate candidate identificationvertical edge detection clan filteringplate candidate segmentationvertical projection acquisition pinnacle clipping of the plateplate skew evaluationhorizontal segmentationplate candidate verificationCray-level distribution consistency considerations